dc.contributor.advisor	Jang, Seung Soon
dc.contributor.advisor	Jones, Christopher W.
dc.contributor.author	Lawler, Robin May
dc.contributor.committeeMember	Kohl, Paul
dc.contributor.committeeMember	Fuller, Thomas
dc.contributor.committeeMember	Sholl, David
dc.contributor.department	Chemical and Biomolecular Engineering
dc.date.accessioned	2022-01-14T16:19:38Z
dc.date.available	2022-01-14T16:19:38Z
dc.date.created	2021-12
dc.date.issued	2022-01-04
dc.date.submitted	December 2021
dc.date.updated	2022-01-14T16:19:38Z
dc.description.abstract	Polymer electrolyte membrane fuel cells (PEMFCs) are predicted to revolutionize energy conversion for transportation due to a multitude of advantages over conventional methods. However, due to their lack of resillience to adverse conditions, they are not as widespread as other portable energy technologies. In order to render PEMFCs suitable for extensive use, we must explore methods to enhance their performance such as improving conductivity in extreme conditions and lengthening their lifetime. This thesis aims to address the issue of PEMFC versatility by using multiscale computational simulations to provide fundamental understanding of PEM mechanisms and suggest superior chemistries for PEM components. Specifically, Aim 1 aids in the design of PEMs resistant to hot or dry conditions by offering novel insight into how PEM nanostructure influences proton transport in low-humidity conditions. Aim 2 involves the elucidation of the CeO2 radical scavenging mechanisms in PEMs, as well as the suggestion of an improved CeO2 surface chemistry. Finally, Aim 3 expands upon our first aim by offering an algorithm which accurately predicts pKa (and, consequently, approximates performance) of acids relevant to PEMs, streamlining the design of novel, durable chemistries.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/66187
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	polymer electrolyte membrane fuel cells
dc.subject	DFT
dc.subject	machine learning
dc.subject	molecular dynamics
dc.title	MULTISCALE COMPUTATIONAL MODELING OF NANOSTRUCTURE AND TRANSPORT IN POLYMER ELECTROLYTE MEMBRANE FUEL CELLS
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Jones, Christopher W.
local.contributor.advisor	Jang, Seung Soon
local.contributor.corporatename	School of Chemical and Biomolecular Engineering
local.contributor.corporatename	College of Engineering
relation.isAdvisorOfPublication	27088bc0-032b-40d1-b0a7-7f2f25b5bdeb
relation.isAdvisorOfPublication	2a440d81-b960-4958-8534-0b207d8488a7
relation.isOrgUnitOfPublication	6cfa2dc6-c5bf-4f6b-99a2-57105d8f7a6f
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level	Doctoral

Title: MULTISCALE COMPUTATIONAL MODELING OF NANOSTRUCTURE AND TRANSPORT IN POLYMER ELECTROLYTE MEMBRANE FUEL CELLS

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MULTISCALE COMPUTATIONAL MODELING OF NANOSTRUCTURE AND TRANSPORT IN POLYMER ELECTROLYTE MEMBRANE FUEL CELLS